Python Quick Review

This crash course will teach you the basics and advanced concepts of Python Programming

Author

Juma Shafara

Published

January 1, 2024

Modified

August 14, 2024

Keywords

python basics, variables, numbers, operators, containers, flow control, advanced, modules, file handling

Introduction

Python is a great general-purpose programming language on its own, but with the help of a few popular libraries (numpy, scipy, matplotlib) it becomes a powerful environment for scientific computing.

Whether you’re a total beginner or seasoned programmer, this lesson will serve as a Python Quick Crash Course to refresh your Python knowledge

In this tutorial, we will cover:

Basic Python: Basic data types (Containers, Lists, Dictionaries, Sets, Tuples), Functions, Classes

A Brief Note on Python Versions

We’ll be using Python 3.10 for this iteration of the course. You can check your Python version at the command line by running python --version.

# checking python version
!python --version

Python 3.12.3

Basics of Python

Python is a high-level, dynamically typed multiparadigm programming language. Python code is often said to be almost like pseudocode, since it allows you to express very powerful ideas in very few lines of code while being very readable. As an example, here is an implementation of the classic quicksort algorithm in Python:

def quicksort(array):
    if len(array) <= 1:
        return array
    pivot = array[len(array) // 2]
    left = [number for number in array if number < pivot]
    middle = [number for number in array if number == pivot]
    right = [number for number in array if number > pivot]
    return quicksort(left) + middle + quicksort(right)

quicksort([3,6,8,10,1,2,1])

[1, 1, 2, 3, 6, 8, 10]

sorted('listen', reverse=True)

['t', 's', 'n', 'l', 'i', 'e']

Variables

Variables are stores of value

name = 'Juma'
age = 19
id_number = 190045

Rules to consider

Variable names should be meaningful eg number instead of x
Variable names should contain only alpha-numberic characters, and maybe under_scores
Variable names can only start with letters or an underscore
Variable name cannot contain special characters
Variables names are case sensitive

Examples of variables

For this course, we’ll use snake case for quick variables

name = 'Eva'
list_of_names = ['Eva', 'Shafara', 'Bob'] # snake case

we’ll use camel case for function variables

def calculateBMI(weight_kg, height_m): # camel case
    bmi = weight_kg / height_m ** 2
    rounded_bmi = round(bmi, 3)
    return rounded_bmi

finally, we’ll use pascal case for class variables

class MathFunction:    # Pascal Case
    def __init__(self, number):
        self.number = number

    def square(self):
        return self.number ** 2

    def cube(self):
        return self.number ** 3

Basic data types

Numbers

Integers and floats work as you would expect from other languages:

number = 3
print('Number: ', number)
print('Type: ', type(number))

Number:  3
Type:  <class 'int'>

# Quick number arithmetics

print(number + 1)   # Addition
print(number - 1)   # Subtraction
print(number * 2)   # Multiplication
print(number ** 2)  # Enumberponentiation

# Some compound assingment operators

number += 1 # number = number + 1
print(number)
number *= 2
print(number)
number /= 1 # number = number / 1
print(number)
number -= 2
print(number)

number = 2.5
print(type(number))
print(number, number + 1, number * 2, number ** 2)

<class 'float'>
2.5 3.5 5.0 6.25

# complex numbers
vector = 2 + 6j
type(vector)

complex

Booleans

Python implements all of the usual operators for Boolean logic, but uses English words rather than symbols:

t, f = True, False
type(t)

bool

Now we let’s look at the operations:

# Logical Operators

print(t and f) # Logical AND;
print(t or f)  # Logical OR;
print(not t)   # Logical NOT;
print(t != f)  # Logical XOR;

False
True
False
True

Strings

A string is a sequence of characters under some quotes. Eg.

hello = 'hello'   # String literals can use single quotes
world = "world"   # or double quotes; it does not matter
print(hello, len(hello))

hello 5

# We can string in python
full = hello + ' ' + world  # String concatenation
print(full)

hello world

hw12 = '{} {} {}'.format(hello, world, 12)  # string formatting
print(hw12)

hello world 12

statement = 'I love to code in {}'
modified = statement.format('JavaScript')
print(modified)

I love to code in JavaScript

# formatting by indexing
statement = '{0} loves to code in {2} and {1}'
statement.format('Juma', 'Python', 'JavaScript')

'Juma loves to code in JavaScript and Python'

# formatting by name
statement = '{name} loves to code in {language1} and {language2}'
statement.format(language2='Python', name='Juma', language1='JavaScript')

'Juma loves to code in JavaScript and Python'

# String Literal Interpolation
name = 'Juma'
language1 = 'JavaScript'
language2 = 'Python'

statement = f'{name} loves to code in {language1} and {language2}'

print(statement)

Juma loves to code in JavaScript and Python

String objects have a bunch of useful methods; for example:

string_ = "hello"
print(string_.capitalize())  # Capitalize a string
print(string_.upper())       # Convert a string to uppercase; prints "HELLO"
print(string_.rjust(7))      # Right-justify a string, padding with spaces
print(string_.center(7))     # Center a string, padding with spaces
print(string_.replace('l', '(ell)'))  # Replace all instances of one substring with another
print('  world '.strip())  # Strip leading and trailing whitespace

Hello
HELLO
  hello
 hello 
he(ell)(ell)o
world

statement = 'i love to code in Python '

capitalized = statement.capitalize()
upped = statement.upper()
replaced = statement.replace('Python', 'javascript')
statement.strip()

'i love to code in Python'

You can find a list of all string methods in the documentation.

Containers

Python containers (collections) are objects that we use to group other objects
Python includes several built-in container types: lists, dictionaries, sets, and tuples.

Lists

A list is an ordered collection of python objects or elements. A list can contain objects of different data types

list_of_numbers = [3, 1, 2]   # Create a list
print(list_of_numbers)
print(list_of_numbers[2])
print(list_of_numbers[-1])     # Negative indices count from the end of the list; prints "2"

[3, 1, 2]
2
2

list_of_numbers[2] = 'foo'    # replacing a specific value in a list
print(list_of_numbers)

[3, 1, 'foo']

list_of_numbers.append('bar') # Add a new element to the end of the list
print(list_of_numbers)

[3, 1, 'foo', 'bar']

last_item = list_of_numbers.pop()     # Remove and return the last element of the list
print(last_item)    # returns the last item 
print(list_of_numbers) # Modifies the original list

bar
[3, 1, 'foo']

Research on:

del
remove()

As usual, you can find all the gory details about lists in the documentation.

Slicing

In addition to accessing list elements one at a time, Python provides concise syntax to access a range of values in a list; this is known as slicing:

list_of_numbers = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
print(list_of_numbers)

[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

print(list_of_numbers)         # Prints "[0, 1, 2, 3, 4]"
print(list_of_numbers[2:4])    # Get a slice from index 2 to 4 (exclusive); prints "[2, 3]"
print(list_of_numbers[2:])     # Get a slice from index 2 to the end; prints "[2, 3, 4]"
print(list_of_numbers[:2])     # Get a slice from the start to index 2 (exclusive); prints "[0, 1]"
print(list_of_numbers[:])      # Get a slice of the whole list; prints ["0, 1, 2, 3, 4]"
print(list_of_numbers[:-1])    # Slice indices can be negative; prints ["0, 1, 2, 3]"
list_of_numbers[2:4] = [8, 9] # Assign a new sublist to a slice
print(list_of_numbers)         # Prints "[0, 1, 8, 9, 4]"

[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
[2, 3]
[2, 3, 4, 5, 6, 7, 8, 9]
[0, 1]
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
[0, 1, 2, 3, 4, 5, 6, 7, 8]
[0, 1, 8, 9, 4, 5, 6, 7, 8, 9]

Loops

A for loop is used to loop through (or iterate) over a sequence of objects (iterable objects). Iterable objects in python include strings, lists, sets etc

You can loop over the elements of a list like this:

list_of_animals = ['cat', 'dog', 'monkey']

for animal in list_of_animals:
    print(animal)

cat
dog
monkey

list_of_numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 0]
list_of_squared_numbers = []

for number in list_of_numbers:
    list_of_squared_numbers.append(pow(number, 2))

list_of_squared_numbers

[1, 4, 9, 16, 25, 36, 49, 64, 81, 0]

If you want access to the index of each element within the body of a loop, use the built-in enumerate function:

animals = ['cat', 'dog', 'monkey']

for index, animal in enumerate(animals):
    print(f'{index}: {animal}')

0: cat
1: dog
2: monkey

List comprehensions:

numbers = [0, 1, 2, 3, 4]
squares = []

for number in numbers:
    squares.append(pow(number, 2))

print(squares)

[0, 1, 4, 9, 16]

You can make this code simpler using a list comprehension:

list_of_numbers = [0, 1, 2, 3, 4]

squares = [pow(number, 2) for number in list_of_numbers]

print(squares)

[0, 1, 4, 9, 16]

List comprehensions can also contain conditions:

numbers = [0, 1, 2, 3, 4]

even_squares = [pow(number, 2) for number in numbers if number % 2 == 0]

print(even_squares)

[0, 4, 16]

Research: How to combine lists

Dictionaries

A dictionary is an unordered and mutable collection of items
A dictionary is created using curly brackets
Each item in a dictionary contains a key/value pair

# creating a dictionary
person = {
    'first_name': 'Juma',
    'last_name': 'Shafara',
    'age': 51,
    'married': True
}
person

{'first_name': 'Juma', 'last_name': 'Shafara', 'age': 51, 'married': True}

# accessing items in a dictionary
first_name = person['first_name']
last_name = person['last_name']
full_name = first_name + ' ' + last_name

# display
full_name

'Juma Shafara'

# add items to a dictionary
person['hobby'] = 'Coding'
person

{'first_name': 'Juma',
 'last_name': 'Shafara',
 'age': 51,
 'married': True,
 'hobby': 'Coding'}

email = person.get('email', 'email not available')
print(email)

email not available

# modifying a value in a dictionay
person['married'] = False
person

{'first_name': 'Juma',
 'last_name': 'Shafara',
 'age': 51,
 'married': False,
 'hobby': 'Coding'}

# remove an item from a dictionary
person.pop('age')
person

{'first_name': 'Juma',
 'last_name': 'Shafara',
 'married': False,
 'hobby': 'Coding'}

Research:

How to remove an item using the del method
How to iterate over objects in a dictionary
Imitate list comprehension with dictionaries

You can find all you need to know about dictionaries in the documentation.

Sets

A set is an unordered, immutable collection of distinct elements.
A set is created using curly braces
The objects are placed inside the brackets and are separated by commas
As a simple example, consider the following:

animals = {'cat', 'dog'}

print('cat' in animals)   # Check if an element is in a set; prints "True"
print('fish' not in animals)  # prints "True"

True
True

animals.add('fish')      # Add an element to a set

print('fish' in animals) # Returns "True"

print(len(animals))       # Number of elements in a set;

True
3

animals.add('cat')       # Adding an element that is already in the set does nothing
print(len(animals)) 
      
animals.remove('cat')    # Remove an element from a set
print(len(animals))

3
2

Research:

How to remove with discard()
How to remove with pop()
How to combine sets/li>
How to get the difference between 2 sets
What happens when we have repeated elements in a set

Loops: Iterating over a set has the same syntax as iterating over a list; however since sets are unordered, you cannot make assumptions about the order in which you visit the elements of the set:

animals = {'cat', 'dog', 'fish'}

for index, animal in enumerate(animals):
    print(f'{index}: {animal}')

0: fish
1: cat
2: dog

Set comprehensions: Like lists and dictionaries, we can easily construct sets using set comprehensions:

from math import sqrt

print({int(sqrt(x)) for x in range(30)})

{0, 1, 2, 3, 4, 5}

Tuples

A tuple is an (immutable) ordered list of values.
A tuple is in many ways similar to a list; one of the most important differences is that tuples can be used as keys in dictionaries and as elements of sets, while lists cannot. Here is a trivial example:

d = {(x, x + 1): x for x in range(10)}  # Create a dictionary with tuple keys
t = (5, 6)       # Create a tuple
print(type(t))
print(d[t])       
print(d[(1, 2)])

<class 'tuple'>
5
1

# t[0] = 1

Research:

Creating a tuple
Access items in a tuple
Negative indexing tuples
Using range of indexes
Getting the length of items in a tuple
Looping through a tuple
Checking if an item exists in a tuple
How to combine tuples
Prove that tuples are immutable

Functions

A function is a group of statements that performs a particular task

Python functions are defined using the def keyword. For example:

def overWeightOrUnderweightOrNormal(weight_kg:float, height_m:float) -> str:
    '''
    Tells whether someone is overweight or underweight or normal
    '''
    height_m2 = pow(height_m, 2)
    bmi = weight_kg / height_m2
    rounded_bmi = round(bmi, 3)
    if bmi > 24:
        return 'Overweight'
    elif bmi > 18:
        return 'Normal'
    else:
        return 'Underweight'

overWeightOrUnderweightOrNormal(67, 1.7)

'Normal'

We will often use functions with optional keyword arguments, like this:

bmi = calculateBMI(height_m=1.7, weight_kg=67)

print(bmi)

23.183

def greet(name:str='You')->str:
    """
    This function greets people by name
    Example1:
    >>> greet(name='John Doe')
    >>> 'Hello John Doe'
    Example2:
    >>> greet()
    >>> 'Hello You'
    """
    return f'Hello {name}'

# greet('Eva')
?greet

Signature: greet(name: str = 'You') -> str
Docstring:
This function greets people by name
Example1:
>>> greet(name='John Doe')
>>> 'Hello John Doe'
Example2:
>>> greet()
>>> 'Hello You'
File:      /tmp/ipykernel_25670/2049930273.py
Type:      function

Classes

In python, everything is an object
We use classes to help us create new object
The syntax for defining classes in Python is straightforward:

class Person:
    first_name = 'John'
    last_name = 'Tong'
    age = 20

# Instantiating a class
object1 = Person()

print(object1.first_name)
print(object1.last_name)
print(object1.age)

print(f'object1 type: {type(object1)}')

John
Tong
20
object1 type: <class '__main__.Person'>

# Instantiating a class
object2 = Person()

print(object2.first_name)
print(object2.last_name)
print(object2.age)

John
Tong
20

class Person:
    def __init__(self, first_name, last_name, age):
        self.first_name = first_name
        self.last_name = last_name
        self.age = age

    def greet(self, name):
        return f'Hello {name}'

object1 = Person('Juma', 'Shafara', 24)
print(object1.first_name)
print(object1.last_name)
print(object1.age)
print(type(object1))

Juma
Shafara
24
<class '__main__.Person'>

object2 = Person('Eva', 'Ssozi', 24)
print(object2.first_name)
print(object2.last_name)
print(object2.age)
print(object2.greet('Shafara'))
print(type(object2))

Eva
Ssozi
24
Hello Shafara
<class '__main__.Person'>

class Student(Person):
    def __init__(self, first_name, last_name, age, id_number, subjects=[]):
        super().__init__(first_name, last_name, age)
        self.id_number = id_number
        self.subjects = subjects

    def addSubject(self, subject):
        self.subjects.append(subject)

student1 = Student('Calvin', 'Masaba', 34, '200045', ['math', 'science'])

student1.addSubject('english')

student1.subjects

['math', 'science', 'english']

Research:

Inheritance: This allows to create classes that inherit the attributes and methods of another class

Introduction

A Brief Note on Python Versions

Don’t Miss Any Updates!

Basics of Python

Variables

Rules to consider

Examples of variables

Basic data types

Numbers

Booleans

Strings

Containers

Lists

Slicing

Loops

List comprehensions:

Dictionaries

Sets

Tuples

Functions

Classes

What’s on your mind? Put it in the comments!